公开(公告)号：WO2013019245A3

公开(公告)日：2014-03-20

申请号：PCT/US2011046907

申请日：2011-08-08

Applicant: PANASONIC CORP ,  LEE KUO-CHU ,  LIU LIPIN ,  OZDEMIR HASAN TIMUCIN ,  YU JANNITE

Inventor： LEE KUO-CHU ,  LIU LIPIN ,  OZDEMIR HASAN TIMUCIN ,  YU JANNITE

IPC: H04N7/18

CPC classification number: G06Q10/06311 ,  G06F21/32 ,  G06Q10/0633 ,  G06Q10/0639 ,  G06Q30/0211 ,  G06Q30/0267 ,  G06Q30/0271 ,  G06Q30/0601 ,  G06Q50/12

Abstract: Method of notifying a user of site abnormalities via an application configured to access an event server having a first sensor abnormality detector connected to a first sensor, for detecting first abnormal behavior of first sub-events sensed by the first sensor, the first abnormal behavior corresponding to a first abnormal behavior value, a second sensor abnormality detector connected to a second sensor, for detecting second abnormal behavior of second sub-events sensed by the second sensor of a type different from the first sensor, the second abnormal behavior corresponding to a second abnormal behavior value, a correlator for correlating the first and second abnormal behavior values and logging correlated values as a composite event, a data store, the application having a viewer configured to show, on the device, data associated with a plurality of composite events, the viewer further configured to display the plurality of composite events in a temporal order.

Abstract translation: 通过配置为访问具有连接到第一传感器的第一传感器异常检测器的事件服务器的应用通知用户站点异常的方法，用于检测由第一传感器感测的第一子事件的第一异常行为，对应于第一异常行为 连接到第二传感器的第二传感器异常检测器，用于检测由第二传感器感测到的与第一传感器不同的类型的第二子事件的第二异常行为，对应于第二异常行为的第二异常行为 异常行为值，用于将第一和第二异常行为值相关联并将相关值记录为复合事件的相关器，数据存储器，具有被配置为在设备上显示与多个复合事件相关联的数据的观看者的应用， 观众还被配置为以时间顺序显示多个复合事件。

公开(公告)号：WO2008103206B1

公开(公告)日：2008-10-30

申请号：PCT/US2007087566

申请日：2007-12-14

Applicant: MATSUSHITA ELECTRIC IND CO LTD ,  OZEDMIR HASAN TIMUCIN ,  KIBEY SAMEER ,  LIU LIPIN ,  LEE KUO CHU ,  MOSALI SUPRAJA ,  JOO NAMSOO ,  LI HONGBING ,  YU JUAN

Inventor： OZEDMIR HASAN TIMUCIN ,  KIBEY SAMEER ,  LIU LIPIN ,  LEE KUO CHU ,  MOSALI SUPRAJA ,  JOO NAMSOO ,  LI HONGBING ,  YU JUAN

IPC: G08B31/00

CPC classification number: G08B31/00 ,  G08B13/196 ,  G08B21/0423

Abstract: A surveillance system generally includes a data capture module that collects sensor data. A scoring engine module receives the sensor data and computes at least one of an abnormality score and a normalcy score based on the sensor data, at least one dynamically loaded learned data model, and a learned scoring method. A decision making module receives the at least one of the abnormality score and the normalcy score and generates an alert message based on the at least one of the abnormality score and the normalcy score and a learned decision making method to produce progressive behavior and threat detection.

Abstract translation: 监视系统通常包括收集传感器数据的数据捕获模块。 评分引擎模块接收传感器数据，并基于传感器数据，至少一个动态加载的学习数据模型和学习评分方法来计算异常分数和正常分数中的至少一个。 决策模块接收异常分数和正常分数中的至少一个，并且基于异常分数和正常分数中的至少一个产生警报消息，以及学习决策方法来产生渐进行为和威胁检测。

公开(公告)号：WO2011102871A1

公开(公告)日：2011-08-25

申请号：PCT/US2010/060745

申请日：2010-12-16

Applicant: PANASONIC CORPORATION ,  LEE, Kuo Chu ,  OZDEMIR, Hasan Timucin ,  SHI, Xiangiun ,  LIU, Lipin ,  JOO, Namsoo ,  YU, Juan ,  LIU, Jun

Inventor： LEE, Kuo Chu ,  OZDEMIR, Hasan Timucin ,  SHI, Xiangiun ,  LIU, Lipin ,  JOO, Namsoo ,  YU, Juan ,  LIU, Jun

IPC: G08B13/196 ,  H04N7/18

CPC classification number: G06T7/2086 ,  G06K9/00771 ,  G06T7/285 ,  G08B13/19608 ,  G08B13/19676

Abstract: A video surveillance system is disclosed. The system includes a model database storing a plurality of models and a vector database storing a plurality of vectors of recently observed trajectories. The system includes a model building module that builds a new motion model corresponding to the motion data of the current trajectory data structure. The system generates a current trajectory data structure having motion data and abnormality scores. The system also includes a database purging module configured to determine a subset of vectors that is most similar to the current trajectory data structure based on a measure of similarity between the subset of vectors and the current trajectory data structure. The database purging module is further configured to replace one of the motion models in the model database with the new motion model based on an amount of vectors in the subset vectors the recentness of the subset of vectors.

Abstract translation: 公开了一种视频监控系统。 该系统包括存储多个模型的模型数据库和存储最近观察到的轨迹的多个矢量的矢量数据库。 该系统包括建立与当前轨迹数据结构的运动数据相对应的新运动模型的模型构建模块。 该系统产生具有运动数据和异常分数的当前轨迹数据结构。 该系统还包括数据库清除模块，其被配置为基于矢量子集与当前轨迹数据结构之间的相似度测量来确定与当前轨迹数据结构最相似的向量子集。 数据库清除模块还被配置为基于子集向量中矢量子集的近似度，用新的运动模型替换模型数据库中的运动模型中的一个。

公开(公告)号：WO2010141117A2

公开(公告)日：2010-12-09

申请号：PCT/US2010/024716

申请日：2010-02-19

Applicant: PANASONIC CORPORATION ,  LEE, Kuo, Chu ,  OZDEMIR, Hasan, Timucin ,  YU, Juan

Inventor： LEE, Kuo, Chu ,  OZDEMIR, Hasan, Timucin ,  YU, Juan

IPC: G06K9/00

CPC classification number: G06K9/00771

Abstract: A system and method for predictive abnormal behavior detection is disclosed. The system receives surveillance data such as video data and can create and update a plurality of prediction models. The system may also receive video data relating to a moving object and may generate a prediction of the future locations of the moving object based on the generated prediction models. The predicted motion may be scored by a scoring engine to determine if the predicted motion is unsafe or otherwise undesirable

Abstract translation: 公开了一种用于预测性异常行为检测的系统和方法。 该系统接收诸如视频数据的监控数据，并且可以创建和更新多个预测模型。 该系统还可以接收与移动对象相关的视频数据，并且可以基于所生成的预测模型生成运动对象的未来位置的预测。 预测的运动可以由评分引擎评分，以确定预测的运动是不安全的还是不希望的

公开(公告)号：WO2010141116A3

公开(公告)日：2010-12-09

申请号：PCT/US2010/024707

申请日：2010-02-19

Applicant: PANASONIC CORPORATION ,  LEE, Kuo Chu ,  OZDEMIR, Hasan Timucin ,  YU, Juan ,  SHI, Xiangjun

Inventor： LEE, Kuo Chu ,  OZDEMIR, Hasan Timucin ,  YU, Juan ,  SHI, Xiangjun

IPC: G06K9/00

Abstract: A surveillance system improves accuracy and robustness of abnormal behavior detection of a monitored object traversing a space includes a metadata processing module, a model building module, and a behavior assessment module. The metadata processing module generates trajectory information for a monitor object and determines attributes of the monitored object. The model building module at least one of generates and updates normal motion models based on at least one of the trajectory information, the attributes, and an abnormal behavior score. The behavior assessment module generates the abnormal behavior score based on one of a plurality of methods. A first one of the plurality of methods defines wrong direction behavior. A second one of the plurality of methods defines wandering/loitering behavior. A third one of the plurality of methods defines speeding behavior.

公开(公告)号：WO2008103206A1

公开(公告)日：2008-08-28

申请号：PCT/US2007/087566

申请日：2007-12-14

Applicant: MATSUSHITA ELECTRIC INDUSTRIAL CO. LTD. ,  OZEDMIR, Hasan Timucin ,  KIBEY, Sameer ,  LIU, Lipin ,  LEE, Kuo Chu ,  MOSALI, Supraja ,  JOO, Namsoo ,  LI, Hongbing ,  YU, Juan

Inventor： OZEDMIR, Hasan Timucin ,  KIBEY, Sameer ,  LIU, Lipin ,  LEE, Kuo Chu ,  MOSALI, Supraja ,  JOO, Namsoo ,  LI, Hongbing ,  YU, Juan

IPC: G08B31/00

CPC classification number: G08B31/00 ,  G08B13/196 ,  G08B21/0423

Abstract: A surveillance system generally includes a data capture module that collects sensor data. A scoring engine module receives the sensor data and computes at least one of an abnormality score and a normalcy score based on the sensor data, at least one dynamically loaded learned data model, and a learned scoring method. A decision making module receives the at least one of the abnormality score and the normalcy score and generates an alert message based on the at least one of the abnormality score and the normalcy score and a learned decision making method to produce progressive behavior and threat detection.

Abstract translation: 监视系统通常包括收集传感器数据的数据捕获模块。 评分引擎模块接收传感器数据并且基于传感器数据，至少一个动态加载的学习数据模型和学习得分方法来计算异常分数和正常分数中的至少一个。 决策制定模块接收异常分数和正常分数中的至少一个，并且基于异常分数和正常分数中的至少一个生成警报消息，以及生成渐进行为和威胁检测的学习决策方法。

公开(公告)号：WO2013019246A1

公开(公告)日：2013-02-07

申请号：PCT/US2011/046910

申请日：2011-08-08

Applicant: PANASONIC CORPORATION ,  LEE, Kuo-Chu ,  MIWA, Michio ,  OZDEMIR, Hasan Timucin ,  YU, Jannite ,  LIU, Lipin

Inventor： LEE, Kuo-Chu ,  MIWA, Michio ,  OZDEMIR, Hasan Timucin ,  YU, Jannite ,  LIU, Lipin

IPC: H04N7/18

CPC classification number: G06Q10/06311 ,  G06K9/00302 ,  G06Q10/06 ,  G06Q30/02 ,  H04N5/23219 ,  H04N7/183

Abstract: A system for improving site operations by detecting abnormalities includes a first sensor abnormality detector connected to a first sensor and configured to learn a first normal behavior sequence, a second sensor abnormality detector connected to a second sensor and configured to learn a second normal behavior sequence, an abnormality correlation server configured to receive abnormally scored first sensor data and abnormally scored second sensor data, the abnormality correlation server further configured to correlate the received abnormally scored first sensor data and abnormally scored second sensor data sensed at the same time by the first and second sensors and determine an abnormal event; and an abnormality report generator configured to generate an abnormality report based on the correlated the received abnormally scored first sensor data and abnormally scored second sensor data.

Abstract translation: 通过检测异常来改善现场操作的系统包括连接到第一传感器并被配置为学习第一正常行为序列的第一传感器异常检测器，连接到第二传感器并被配置为学习第二正常行为序列的第二传感器异常检测器， 异常相关服务器，被配置为接收异常计分的第一传感器数据和异常刻痕的第二传感器数据，所述异常相关服务器还被配置为将接收到的异常打分的第一传感器数据和异步拍摄的第二传感器数据同时被第一和第二传感器数据相关联 传感器并确定异常事件; 以及异常报告发生器，被配置为基于所接收的异常拍摄的第一传感器数据和异常刻痕的第二传感器数据的相关性来生成异常报告。

公开(公告)号：WO2010141116A2

公开(公告)日：2010-12-09

申请号：PCT/US2010024707

申请日：2010-02-19

Applicant: PANASONIC CORP ,  LEE KUO CHU ,  OZDEMIR HASAN TIMUCIN ,  YU JUAN ,  SHI XIANGJUN

Inventor： LEE KUO CHU ,  OZDEMIR HASAN TIMUCIN ,  YU JUAN ,  SHI XIANGJUN

IPC: G06K9/00

CPC classification number: G06T7/20 ,  G06K9/00771 ,  G08B13/19608 ,  G08B13/19613 ,  G08B13/19641 ,  H04N7/181

Abstract: A surveillance system improves accuracy and robustness of abnormal behavior detection of a monitored object traversing a space includes a metadata processing module, a model building module, and a behavior assessment module. The metadata processing module generates trajectory information for a monitor object and determines attributes of the monitored object. The model building module at least one of generates and updates normal motion models based on at least one of the trajectory information, the attributes, and an abnormal behavior score. The behavior assessment module generates the abnormal behavior score based on one of a plurality of methods. A first one of the plurality of methods defines wrong direction behavior. A second one of the plurality of methods defines wandering/loitering behavior. A third one of the plurality of methods defines speeding behavior.

Abstract translation: 监视系统提高了穿过空间的被监视对象的异常行为检测的精度和鲁棒性，包括元数据处理模块，模型构建模块和行为评估模块。 元数据处理模块生成监视对象的轨迹信息，并确定被监视对象的属性。 模型构建模块至少基于轨迹信息，属性和异常行为得分中的至少一个来生成和更新正常运动模型。 行为评估模块基于多种方法之一产生异常行为得分。 多种方法中的第一种方法定义了错误的方向行为。 多种方法中的第二种方法定义了流浪/游荡行为。 多种方法中的第三种方法定义了超速行为。

公开(公告)号：WO2009105299A4

公开(公告)日：2009-12-17

申请号：PCT/US2009031436

申请日：2009-01-20

Applicant: PANASONIC CORP ,  YU JUAN ,  LEE KUO-CHU ,  LI HONGBING ,  OZDEMIR HASAN T ,  LIU LIPIN

Inventor： YU JUAN ,  LEE KUO-CHU ,  LI HONGBING ,  OZDEMIR HASAN T ,  LIU LIPIN

IPC: G06K9/00 ,  G08B13/18

CPC classification number: G06K9/00771 ,  A61B5/1128 ,  A61B5/16 ,  A61B5/7267 ,  G06K9/00785

Abstract: A surveillance system implements an architecture and process to support real-time abnormal behavior assessment operations in a distributed scalable sensor network. An automated behavior model builder generates behavior models from sensor data. A plurality of abnormal behavior scoring engines operating concurrently to generate abnormal behavior assessment models by scoring the behavior models. An execution performance manager performs fast switching of behavior models for the abnormal behavior scoring engines. The execution performance manager performs detection of abnormal behavior score distribution characteristic deviation by comparing a current abnormal behavior assessment model to a pre-recorded abnormal behavior assessment model. The execution performance manager selects a pre-recorded behavior model for the abnormal behavior scoring engines when the deviation exceeds a predetermined threshold.

Abstract translation: 监控系统采用架构和流程来支持分布式可扩展传感器网络中的实时异常行为评估操作。 自动行为模型构建器根据传感器数据生成行为模型。 多个异常行为评分引擎同时操作以通过对行为模型进行评分来生成异常行为评估模型。 执行性能管理器为异常行为评分引擎执行行为模型的快速切换。 执行性能管理器通过将当前异常行为评估模型与预先记录的异常行为评估模型进行比较来执行对异常行为评分分布特征偏差的检测。 当偏差超过预定阈值时，执行表现管理器为异常行为评分引擎选择预先记录的行为模型。

公开(公告)号：WO2009137118A1

公开(公告)日：2009-11-12

申请号：PCT/US2009/031437

申请日：2009-01-20

Applicant: PANASONIC CORPORATION ,  OZDEMIR, Hasan T. ,  LI, Hongbing ,  LEE, Kuo-chu ,  LIU, Lipin ,  JOO, Namsoo

Inventor： OZDEMIR, Hasan T. ,  LI, Hongbing ,  LEE, Kuo-chu ,  LIU, Lipin ,  JOO, Namsoo

IPC: G06K9/00

CPC classification number: G06K9/00771 ,  G06K9/00335

Abstract: A multi-perspective context sensitive behavior assessment system includes an adaptive behavior model builder establishing a real-time reference model that captures intention of motion behavior. It operates by modeling outputs of multiple user defined scoring functions with respect to multiple references of application specific target areas of interest. The target areas have criticality values representing a user's preference regarding the target areas with respect to one another. The outputs of the scoring functions are multiplied by the critically values to form high level sequences of representation that are communicated to the user.

Abstract translation: 多视角上下文敏感行为评估系统包括建立实时参考模型的自适应行为模型构建器，其捕获运动行为的意图。 它通过针对感兴趣的应用程序特定目标区域的多个引用对多个用户定义的评分函数的输出进行建模来进行操作。 目标区域具有表示用户相对于彼此的目标区域的偏好的临界值。 评分函数的输出乘以临界值以形成传达给用户的高级表示序列。